Open Data supplied by Natural Environment Research Council (NERC)

Neil Brown MK3 CTD

The Neil Brown MK3 conductivity-temperature-depth (CTD) profiler consists of an integral unit containing pressure, temperature and conductivity sensors with an optional dissolved oxygen sensor in a pressure-hardened casing. The most widely used variant in the 1980s and 1990s was the MK3B. An upgrade to this, the MK3C, was developed to meet the requirements of the WOCE project.

The MK3C includes a low hysteresis, titanium strain gauge pressure transducer. The transducer temperature is measured separately, allowing correction for the effects of temperature on pressure measurements. The MK3C conductivity cell features a free flow, internal field design that eliminates ducted pumping and is not affected by external metallic objects such as guard cages and external sensors.

Additional optional sensors include pH and a pressure-temperature fluorometer. The instrument is no longer in production, but is supported (repair and calibration) by General Oceanics.

Data Processing

For each station, the CTD data were processed in as close to real time as possible in order to check that all sensors were functioning within acceptable ranges. Raw data were read in for CTD, winch and bottle events. Data were merged using time stamps. Initial conductivity calibration was chosen after the first test station to give a sensible deep T-S (temperature-salinity) value in the Bay of Biscay, based on historical data. While rather crude, the large salinity signal in the work area meant this was acceptable for an initial salinity calibration. Initial oxygen calibration was meaningless. Oxygen sample data were only merged with CTD data right at the end of the cruise, so calibration of CTD oxygen had to wait for post-cruise processing at SOC.

Working files on board ship consisted of cleaned and de-spiked 1 Hz data, and extracted downcast data, sorted, averaged to 2 db and interpolated to fill any gaps. It was noted that the apparent T-S relation was drifting more than would be considered acceptable for highest-quality deep hydrography. This was attributed to a failing conductivity cell. However, the effect was not so great that the drift could not be satisfactorily monitored from the sample salinities. Deep03 with a single conductivity cell was kept in use until the end of this cruise, and the need for the cell to be changed prior to the next cruise was noted. Data cycles that define the downcast portion of the 1 Hz file were checked in post cruise processing, and a few errors corrected.

Salinity Calibration

The shortness of the working time (8 days) for CTD measurements during Discovery 232 meant that rather little shipboard calibration work was done. Initial comparisons between sample and CTD salinities revealed the problem with the conductivity cell, which was due to be changed for cruise 233. Detailed comparisons were carried out post-cruise by Dr. King at SOC. CTD bottle firing data were extracted by time and compared with sample salinity. Since the stations are relatively shallow and the temperature range is relatively small, a simple salinity offset was identified for each station, rather than attempting a more complicated fit between CTD and sample conductivity. The complete data processing path was then repeated automatically, so that CTD data from bottle firing events was extracted from the new 1 Hz files and passed into the sample files. This was necessary to ensure that correct CTD salinities were available for all bottles, including, for example, trace metal bottles from which salinity samples had not been drawn.

Care was needed to exclude unsuitable salinity samples from the calibration process. Strong vertical gradients in salinity, as large as 1 over 10 metres in the vertical, are not well sampled by 10-litre Niskin bottles. Estimates from previous cruises (e.g. Saunders et al., 1993) suggest that the vertical flushing distance of the bottles is 5 metres or more. Thus, sample minus CTD discrepancies up to, or even greater than, 0.1 can arise from this source of error. As individual stations were examined, large residuals in regions of strong gradient were noted and excluded from the calibration. However, these sample data were not flagged as bad, since there is no reason to suspect that either the sample capture or the sample analysis were faulty.

Residuals between final CTD and the subset of sample salinities used in the calibration showed a typical standard deviation of less than 0.004, for up to 8 sample salinities per cast. This represents the sum of CTD salinity errors, sample analysis errors, and sample/CTD mismatches arising from smaller vertical gradients that have not already been excluded. Final CTD data were produced for the 27 stations in the work area.

Oxygen Calibration

No oxygen calibration was attempted at sea, because the sample data were not available until close to the end of the cruise in Tenerife. Post-cruise at SOC, CTD oxygen was calibrated station by station by Dr. King. Up to 5 oxygen parameters (S(1) to S(5)) were fitted for each station, using the following expression:

The requirement is to fit downcast CTD oxygen data from the 2 dbar file, which are the reported CTD oxygen data, to the samples collected on the upcast.

The result of fitting the oxygen algorithm parameters was examined on each station. On some stations, the distribution of sample values and CTD values made the fitting problem ill-conditioned, so that one or more of the parameters could not be determined. In these cases, subjective judgement was used and those parameters were fixed at values representative of nearby stations. Remaining parameters were then fitted to the available data. As with salinity calibration, outliers were identified and excluded from the fitting procedure, which was then repeated. Where the outlier was attributed to a bad sample analysis, the sample flag was set to `bad'. Typical rms residuals per station in the finished dataset are less than 3.5 umol/l, where the mean residual is calculated using number of degrees of freedom = Number of samples - 5.

Some final fixes were required. On some stations, near-surface CTD oxygen data were bad, arising from the CTD being soaked at 10 metres, but then not being returned to surface before commencing the downcast. Near-surface data, acquired before soaking, were deleted and replaced by the shallowest good data. Therefore, the 2db CTD oxygen data on these stations (13375, 381, 382, 392, 395, 396, 397, 406, 407) do not correspond to the oxyc data in the files. In addition, a few residual spikes were removed by manual editing. At station 408, no oxygen samples were drawn because it was a repeat of station 404. Appropriate `fake' sample data at bottle closing depths were invented by examining T-O relation on station 404, so that CTD oxygen could be calibrated.

Lastly, CTD oxygens were fitted to sample oxygen reported in umol/l. At the time of this report, sample and CTD oxygen data are still stored as umol/l. These should subsequently be converted to umol/kg, using a density based on the recorded temperatures at the time of fixing the samples.

B.A. King, K.M. White and S. Watts

General Data Screening carried out by BODC

BODC screen both the series header qualifying information and the parameter values in the data cycles themselves.

Header information is inspected for:

Irregularities such as unfeasible values

Inconsistencies between related information, for example:

Times for instrument deployment and for start/end of data series

Length of record and the number of data cycles/cycle interval

Parameters expected and the parameters actually present in the data cycles

Originator's comments on meter/mooring performance and data quality

Documents are written by BODC highlighting irregularities which cannot be resolved.

Data cycles are inspected using time or depth series plots of all parameters. Currents are additionally inspected using vector scatter plots and time series plots of North and East velocity components. These presentations undergo intrinsic and extrinsic screening to detect infeasible values within the data cycles themselves and inconsistencies as seen when comparing characteristics of adjacent data sets displaced with respect to depth, position or time. Values suspected of being of non-oceanographic origin may be tagged with the BODC flag denoting suspect value; the data values will not be altered.

The following types of irregularity, each relying on visual detection in the plot, are amongst those which may be flagged as suspect:

If a large percentage of the data is affected by irregularities then a Problem Report will be written rather than flagging the individual suspect values. Problem Reports are also used to highlight irregularities seen in the graphical data presentations.

Inconsistencies between the characteristics of the data set and those of its neighbours are sought and, where necessary, documented. This covers inconsistencies such as the following:

Maximum and minimum values of parameters (spikes excluded).

The occurrence of meteorological events.

This intrinsic and extrinsic screening of the parameter values seeks to confirm the qualifying information and the source laboratory's comments on the series. In screening and collating information, every care is taken to ensure that errors of BODC making are not introduced.